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Writing triskele wrapper in Notebook

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Florent Guiotte 2018-03-19 18:34:02 +01:00
parent ea29c16f2a
commit 9d63fbea43
1 changed files with 143 additions and 1 deletions
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144
Notebooks/TRYSKELE Wrapper.ipynb
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@ -1,11 +1,153 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# TRYSKELE Wrapper\n",
"\n",
"Dependence \n",
"--\n",
"\n",
"`tryskele` project folder (compiled) in jupyter's root directory. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
"source": [
"from pathlib import Path\n",
"import subprocess\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"triskele_bin = Path('../triskele/build/out/apGenerator')\n",
"triskele_bin.exists()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"process = [triskele_bin.absolute(),\n",
" '']\n",
"\n",
"tryskele = subprocess.Popen(process, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n",
"print('STDOUT:\\n' + tryskele.stdout.read().decode() + '\\nSTDERR:\\n' + tryskele.stderr.read().decode())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"area = np.array([42,100,1000])\n",
"np.savetxt(area_conf, area)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Files\n",
"infile = Path('../Data/phase1_rasters/DEM_C123_TLI/UH17_GEG05_TR.tif')\n",
"outfile = Path('../Res/out.tiff')\n",
"\n",
"area_conf = Path('../Res/area.txt')\n",
"deviation_conf = Path('../Res/deviation.txt')\n",
"inertia_conf = Path('../Res/inertia.txt')\n",
"\n",
"# Attributes definition\n",
"area = np.arange(100)#np.array([10,100,1000])\n",
"deviation = np.array([10,100,1000])\n",
"inertia = np.array([10,100,1000])\n",
"np.savetxt(area_conf, area, fmt='%d')\n",
"np.savetxt(deviation_conf, deviation, fmt='%d')\n",
"np.savetxt(inertia_conf, inertia, fmt='%d')\n",
"\n",
"process = [triskele_bin.absolute(),\n",
" '-i', infile.absolute(),\n",
" '--tos-tree',\n",
" '--area', area_conf.absolute(),\n",
" '--standard-deviation', deviation_conf.absolute(),\n",
" '--moment-of-inertia', inertia_conf.absolute(),\n",
" '-o', outfile.absolute()]\n",
"\n",
"tryskele = subprocess.Popen(process, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n",
"print('STDOUT:\\n' + tryskele.stdout.read().decode() + '\\nSTDERR:\\n' + tryskele.stderr.read().decode())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np.expand_dims(out[:,:,0] < 50, axis=2).shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"out = plt.imread(outfile.absolute())\n",
"display(out.shape)\n",
"\n",
"dwidth = 32\n",
"plt.figure(figsize=(dwidth, dwidth * out.shape[0] / out.shape[1] * .80))\n",
"#plt.figure(figsize=(16,9))\n",
"\n",
"display_channel = 2\n",
"plt.imshow(out[:,:,display_channel] * (out[:,:,display_channel] < 50))\n",
"plt.colorbar()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"out_df = pd.DataFrame(out.reshape(-1, out.shape[2]))\n",
"out_df.describe()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np.unique(out_df, return_counts=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.hist(out_df[0] * out_df[0] , 256, log=True)\n",
"plt.show()"
]
}
],
"metadata": {